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Knowledge Discovery Database (KDD)-Data Mining Application in Transportation

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dc.contributor.author Fauziah Abdul Rahman, Mohammad Ishak Desa
dc.contributor.author Antoni Wibowo, Norhaidah Abu Haris
dc.date.accessioned 2014-10-30T05:09:19Z
dc.date.available 2014-10-30T05:09:19Z
dc.date.issued 2014-10-30
dc.identifier.uri http://localhost/xmlui/handle/123456789/8130
dc.description Conference venue:Yogjakarta en_US
dc.description.abstract In this paper, an understanding and a review of data mining (DM) development and its applications in logistics and specifically transportation are highlighted. Even though data mining has been successful in becoming a major component of various business processes and applications, the benefits and real-world expectations are very important to consider. It is also surprising to note that very little is known to date about the usefulness of applying data mining in transport related research. From the literature, the frameworks for carrying out knowledge discovery and data mining have been revised over the years to meet the business expectations. In this paper, we apply CRISP-DM for formulating effective tire maintenance strategy within the context of a Malaysian’s logistics company. The results of applying CRISP-DM for tire maintenance decisions are presented and discussed. en_US
dc.subject Data Mining en_US
dc.subject Knowledge Discovery Database- Data Mining (KDD-DM) en_US
dc.subject Domain-Driven Data Mining (DDDM) en_US
dc.subject Actionable Knowledge Discovery (AKD) en_US
dc.subject Actionable Knowledge Discovery (AKD) en_US
dc.title Knowledge Discovery Database (KDD)-Data Mining Application in Transportation en_US
dc.conference.name Proceeding of International Conference on Electrical Engineering Computer Science and Informatics en_US
dc.conference.year 2014 en_US


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